title: Mortality incidence and the severity of coronary atherosclerosis assessed by computed tomography angiography.
abstract: OBJECTIVE
  This study investigated whether cardiac computed tomography angiography (CTA) can predict all-cause mortality in symptomatic patients.
  
  
  BACKGROUND
  Noninvasive coronary angiography is being increasingly performed by CTA to assess for obstructive coronary artery disease (CAD), and minimal outcome data exist for coronary CTA. We have utilized a cohort of symptomatic patients who underwent electron beam tomography to allow for longer follow-up (up to 12 years) than currently available with newer 64-slice multidetector-row computed tomography studies.
  
  
  METHODS
  In all, 2,538 consecutive patients who underwent CTA by electron beam tomography (age 59 +/- 14 years, 70% males) without known CAD were studied. Computed tomographic angiography results were categorized as significant CAD (> or =50% luminal narrowing), mild CAD (<50% stenosis), and normal coronary arteries. Multivariable Cox proportional hazards models were developed to predict all-cause mortality. Risk-adjusted models incorporated traditional risk factors for coronary disease and coronary artery calcification (CAC).
  
  
  RESULTS
  During a mean follow-up of 78 +/- 12 months, the death rate was 3.4% (86 deaths). The CTA-diagnosed CAD was an independent predictor of mortality in a multivariable model adjusted for age, gender, cardiac risk factors, and CAC (p < 0.0001). The addition of CAC to CTA-diagnosed CAD increased the concordance index significantly (0.69 for risk factors, 0.83 for the CTA-diagnosed CAD, and 0.89 for the addition of CAC to CAD, p < 0.0001). Risk-adjusted hazard ratios for CTA-diagnosed CAD were 1.7-, 1.8-, 2.3-, and 2.6-fold for 3-vessel nonobstructive, 1-vessel obstructive, 2-vessel obstructive, and 3-vessel obstructive CAD, respectively (p < 0.0001), when compared with the group who did not have CAD.
  
  
  CONCLUSIONS
  The primary results of our study reveal that the burden of angiographic disease detected by CTA provides both independent and incremental value in predicting all-cause mortality in symptomatic patients independent of age, gender, conventional risk factors, and CAC.
authors.affiliation: Division of Cardiology, Department of Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA.
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Ostrom
authors.forename: Ambarish
authors.initials: A
authors.lastname: Gopal
authors.forename: Naser
authors.initials: N
authors.lastname: Ahmadi
authors.forename: Khurram
authors.initials: K
authors.lastname: Nasir
authors.forename: Eric
authors.initials: E
authors.lastname: Yang
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kakadiaris
authors.forename: Ferdinand
authors.initials: F
authors.lastname: Flores
authors.forename: Song S
authors.initials: SS
authors.lastname: Mao
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Budoff
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002423:Cause of Death; D015331:Cohort Studies; D016001:Confidence Intervals; D003287:Contrast Media / Q000494:pharmacology; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000401:mortality* / Q000503:physiopathology; D005260:Female; D006801:Humans; D015994:Incidence; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D011856:Radiographic Image Enhancement; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D012737:Sex Factors; D016019:Survival Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media